No abstract

Among 114 clinical Neisseria gonorrhoeae isolates collected in Vietnam during 2019–2020, we detected 15 of subclone sequence type 13871 of the FC428 clonal complex. Fourteen sequence type 13871 isolates with mosaic penA allele 60.001 were ceftriaxone or cefixime nonsusceptible, and 3/14 were azithromycin nonsusceptible. Emergence of this subclone threatens treatment effectiveness.

Coastline is the most dynamic part of seascape since its shape is affected by various factors. Coastal zone is an area with immense geological, geomorphological and ecological interest. Monitoring coastal change is very important for safe navigation, coastal resource management. This paper shows a result of monitoring coastal morphological changes using Remote Sensing and GIS. Study was carried out to obtain intensity of erosion, deposition and sand bar movement in the Red River Delta. Satellite images of ALOS/AVNIR-2 and Landsat were used for the monitoring of coastal morphological changes over the period of 1975 to 2009. Band rationing and threshold technique was used for the coastline extraction. Tidal levels at the time of image acquisition varied from -0.89m to 2.87m. Therefore, coastline from another image at a different tidal level in the same year was considered to get the corrected coastline by interpolation technique. A series of points were generated along the coastal line from 1975 image and were established as reference points to see the change in later periods. The changes were measured in Euclidean distances from these reference points. Positive values represented deposition to the sea and negative values are erosion. The result showed that the Red river delta area expanded to the sea 3500m in

In recent years, the Lam river basin had suffered various forms of natural disasters such as floods, inundations, windstorms, tornadoes, etc. Among all these, the flood has proved to be the greatest threat to the people and the socio-economic development in the basin. Moreover, it is very frequent as compared to other natural disasters. In view of the fact that such disastrous floods are still occurring in the basin, it becomes a necessity to determine the causes and analyze the components affecting flood. This is important in order to develop an early flood warning system and thus minimize the negative impact of flood in the Lam river basin on the people and the facilities. In this paper, the Analytical Hierarchy Process (AHP) analysis method integrated with GIS technology is used to map flood risk zones in the Lam river basin. The parameters used for the analysis are the main causes affecting the floods. In addition to the 5 most commonly used factors such as slope, rainfall, land cover, soil, and drainage density, this study also includes a new factor - relative slope length to compute a more rigorous and reliable model. The results were compared with the two more methods of flood hazard zoning in the same study area: the method of the main flood caused factor analysis and the method of inheriting, data analyzing, and processing. The results were also validated by the historical flood data of three years 2010, 2013, and 2016.

Land cover is a critical factor for climate change and hydrological models. The extraction of land cover data from remote sensing images has been carried out by specialized commercial software. However, the limitations of computer hardware and algorithms of the commercial software are costly and make it take a lot of time, patience, and skills to do the classification. The cloud computing platform Google Earth Engine brought a breakthrough in 2010 for analyzing and processing spatial data. This study applied Object-based Random Forest classification in the Google Earth Engine platform to produce land cover data in 2010 in the Vu Gia - Thu Bon river basin. The classification results showed 7 categories of land cover consisting of plantation forest, natural forest, paddy field, urban residence, rural residence, bare land, and water surface, with an overall accuracy of 73.9% and kappa of 0.70.